Many liquid metals have a high boiling point,strong electrical conductivity,high thermal conductivity,and nontoxic properties,which make them ideal targets for applications in different fields such as optics,microcir...Many liquid metals have a high boiling point,strong electrical conductivity,high thermal conductivity,and nontoxic properties,which make them ideal targets for applications in different fields such as optics,microcircuits,electronic switches,micro-electromechanical System(MEMS)devices and 3D printing manufacturing.However,owing to the generally high surface tension of these liquids,achieving uniform micro-droplets is often a challenge due to the inherent difficulties in controlling their size and shape.In this study,a gallium indium alloy(GaIn24.5)has been used in combination with a pneumatic drop-on-demand(DOD)injection technology to carry out a series of experiments.The micro-droplet forming process has been explored for different pressure and pulse width conditions.Uniform metal droplets(diameter 1080μm)have been obtained with a 1.5 kPa jet pressure,100 ms pulse width,and 50%duty ratio.The standard deviation of the measured metal droplets diameter has been found to be approximately 20μm.展开更多
展开互质阵列将两个子阵完全展开,因而可在阵元数目受限情况下获得相较于均匀阵列以及传统互质阵列更大的阵列孔径。文中基于双基地展开互质阵列多输入多输出(Multiple Input Multiple Output,MIMO)雷达阵列结构,提出了基于降维多重信...展开互质阵列将两个子阵完全展开,因而可在阵元数目受限情况下获得相较于均匀阵列以及传统互质阵列更大的阵列孔径。文中基于双基地展开互质阵列多输入多输出(Multiple Input Multiple Output,MIMO)雷达阵列结构,提出了基于降维多重信号分类(Multiple Signal Classification,MUSIC)算法的双基地展开互质阵列MIMO雷达离开角(Direction of Departure,DOD)、到达角(Direction of Arrival,DOA)联合估计算法。算法通过增加约束并构造代价函数的方式,将二维MUSIC算法中的穷尽搜索二维谱峰转化为求解带约束二次优化问题,先后得到DOA、DOD,并且DOD与DOA自动配对。降维思想的引入使得算法无需二维搜索,因而复杂度显著下降。同时,得益于展开互质阵列MIMO雷达形成的虚拟阵列与大幅扩展的阵列孔径,文中提出的算法亦获得了显著提升的分辨率、自由度以及低信噪比下更为优异的估计性能。此外,子阵数目的互质消除了阵元间距大于半波长可能导致的相位模糊问题。仿真验证了算法的有效性。展开更多
多输入多输出(Multiple-input multiple-output,MIMO)雷达利用多个天线发送和接收信号,具有超过传统相控阵的潜在优势。本文提出一种双基地MIMO雷达中基于传播算子的离开角(Direction of departure,DOD)和到达角(Direction of arrival,D...多输入多输出(Multiple-input multiple-output,MIMO)雷达利用多个天线发送和接收信号,具有超过传统相控阵的潜在优势。本文提出一种双基地MIMO雷达中基于传播算子的离开角(Direction of departure,DOD)和到达角(Direction of arrival,DOA)估计算法。该算法利用传播因子避免了对协方差矩阵特征值分解降低了运算的复杂度,并且在低信噪比和低快拍数的情况下,该算法仍具有良好的性能。与快速多目标定位算法相比,本文算法的角度估计性能有很大的提高。文中还推导出了离开角和到达角估计的均方误差。仿真结果证明了该算法的有效性。展开更多
实值处理具有降低高自由度多输入多输出(multiple-input multiple-output,MIMO)雷达角度估计大计算量的优势。但受制于阵列的共轭对称性,对于任意阵列结构的双基地MIMO雷达发射角(direction of departure,DOD)和接收角(direction of arr...实值处理具有降低高自由度多输入多输出(multiple-input multiple-output,MIMO)雷达角度估计大计算量的优势。但受制于阵列的共轭对称性,对于任意阵列结构的双基地MIMO雷达发射角(direction of departure,DOD)和接收角(direction of arrival,DOA)联合估计,若不做附加的预处理则无法实现实值操作,故将常规阵列实值处理的多重信号分类(multiple signal classification,MUSIC)超分辨算法推广至任意阵列结构的双基地MIMO雷达。首先根据MIMO雷达的导向矢量共轭与镜像的对等性,提取接收信号协方差矩阵的实部,并对其进行特征分解得到"目标加倍"的信号子空间及其应对的噪声子空间;然后利用Kronecker积的特性对其进行降维处理,得到搜索区域减半的一维半实值域MUSIC谱,取出目标DOD真值与其镜像代入降维Capon算法来剔除虚拟峰值得到目标DOD估计真值;最后利用特征矢量得到模糊DOA估计值,采用方向余弦差最小范数方法得到目标DOA无模糊估计值。本文算法估计性能与一维搜索复数域MUSIC相当,计算量约降50%,且能够实现DOD和DOA的自动配对。仿真结果证明了该算法的有效性。展开更多
Over the course of millions of years,nature has evolved to ensure survival and presents us with a myriad of functional surfaces and structures that can boast high efficiency,multifunctionality,and sustainability.What ...Over the course of millions of years,nature has evolved to ensure survival and presents us with a myriad of functional surfaces and structures that can boast high efficiency,multifunctionality,and sustainability.What makes these surfaces particularly practical and effective is the intricate micropatterning that enables selective interactions with microstructures.Most of these structures have been realized in the laboratory environment using numerous fabrication techniques by tailoring specific surface properties.Of the available manufacturing methods,additive manufacturing(AM)has created opportunities for fabricating these structures as the complex architectures of the naturally occurring microstructures far exceed the traditional ways.This paper presents a concise overview of the fundamentals of such patterned microstructured surfaces,their fabrication techniques,and diverse applications.A comprehensive evaluation of micro fabrication methods is conducted,delving into their respective strengths and limitations.Greater emphasis is placed on AM processes like inkjet printing and micro digital light projection printing due to the intrinsic advantages of these processes to additively fabricate high resolution structures with high fidelity and precision.The paper explores the various advancements in these processes in relation to their use in microfabrication and also presents the recent trends in applications like the fabrication of microlens arrays,microneedles,and tissue scaffolds.展开更多
结合分布式阵列和双基地多输入多输出(Multiple-Input Multiple-Output,MIMO)雷达的特点,提出了一种新的双基地分布式阵列MIMO雷达的接收角(Direction of Arrival,DOA)和发射角(Direction of Departure,DOD)估计方法.根据发射阵列和接...结合分布式阵列和双基地多输入多输出(Multiple-Input Multiple-Output,MIMO)雷达的特点,提出了一种新的双基地分布式阵列MIMO雷达的接收角(Direction of Arrival,DOA)和发射角(Direction of Departure,DOD)估计方法.根据发射阵列和接收阵列的空域旋转不变特性,利用旋转不变估计技术(Estimation of Signal Parameters via Rotational Invariance Techniques,ESPRIT)获取无模糊DOA粗估计和高精度周期性模糊的DOA、DOD精估计;再利用无模糊DOA粗估计、目标的双基地距离信息以及双基地MIMO雷达的几何特点,解除DOA、DOD精估计的周期性模糊,得到高精度且无模糊的DOA和DOD估计.最后,根据ESPRIT算法原理和估计误差的概率统计特性进行算法的性能分析,给出算法基线模糊门限的近似计算方法.该算法有效地放宽了发射阵列孔径扩展程度的限制,从而提高了阵列在大孔径下的角度估计精度,且能够实现DOA和DOD估计的自动配对.仿真结果验证了所提算法和性能分析方法的有效性.展开更多
Lithium element has attracted remarkable attraction for energy storage devices, over the past 30 years. Lithium is a light element and exhibits the low atomic number 3, just after hydrogen and helium in the periodic t...Lithium element has attracted remarkable attraction for energy storage devices, over the past 30 years. Lithium is a light element and exhibits the low atomic number 3, just after hydrogen and helium in the periodic table. The lithium atom has a strong tendency to release one electron and constitute a positive charge, as Li<sup> </sup>. Initially, lithium metal was employed as a negative electrode, which released electrons. However, it was observed that its structure changed after the repetition of charge-discharge cycles. To remedy this, the cathode mainly consisted of layer metal oxide and olive, e.g., cobalt oxide, LiFePO<sub>4</sub>, etc., along with some contents of lithium, while the anode was assembled by graphite and silicon, etc. Moreover, the electrolyte was prepared using the lithium salt in a suitable solvent to attain a greater concentration of lithium ions. Owing to the lithium ions’ role, the battery’s name was mentioned as a lithium-ion battery. Herein, the presented work describes the working and operational mechanism of the lithium-ion battery. Further, the lithium-ion batteries’ general view and future prospects have also been elaborated.展开更多
频控阵(Frequency Diversity Array,FDA)雷达于2006年由Antonik和Wicks提出.由于FDA雷达每个相邻的天线之间存在一个频率偏移,因此在发射阵列存在距离角度二维依赖性.而对于双基地频控阵多输入多输出(FDA-Multiple Input Multiple Outpu...频控阵(Frequency Diversity Array,FDA)雷达于2006年由Antonik和Wicks提出.由于FDA雷达每个相邻的天线之间存在一个频率偏移,因此在发射阵列存在距离角度二维依赖性.而对于双基地频控阵多输入多输出(FDA-Multiple Input Multiple Output,FDA-MIMO)雷达而言,在导向矢量中耦合了波离方向、到达方向、距离(Direction Of Departure-Direction Of Arrival-range,DOD-DOA-range)三个信息,如何对三者信息进行解耦便成为研究的重点.本文针对双基地FDA-MIMO雷达的目标参数估计问题,提出了一个张量框架下的降维多重信号分类(Reduced-Dimension MUltiple SIgnal Classification,RD-MUSIC)的参数估计算法.首先,为了将发射阵列中的DOD和距离信息进行解耦,需要对发射阵列进行子阵的划分.紧接着利用高阶奇异值分解(High-Order-Singular Value Decomposition,HOSVD)算法获得信号子空间,并构建二维空间谱函数.其次,通过拉格朗日算法对空间谱进行降维,使其仅与DOA有关,从而得到DOA估计.然后利用子阵之间的频率增量来对DOD和距离信息进行解耦,同时消除相位模糊,最终得到与DOA估计自动匹配的DOD和距离估计.所提算法利用高维数据的多维结构提高了估计精度,同时能够有效地降低运算复杂度.数值实验证明了所提算法性能的优越性.展开更多
基金the National Natural Science Foundation of China(Grant Nos.51305128 and 52005059)the China Postdoctoral Science Foundation(Grant No.2020M673127)+5 种基金the Natural Science Foundation of Chongqing(Grant No.cstc2020jcyj-bshX0008)the Fundamental Research Funds for the Central Universities of China(Grant No.2020CDJQYA035)the key scientific and technological project of Henan province(Grant No.192102210055)the“Construction of double city economic circle in Chengdu Chongqing area”scientific and technological innovation project(Grant No.KJCXZD2020011)the key scientific research projects of the colleges and universities of Henan province(Grant No.18A4600050)Outstanding Young Backbone Teachers projects of Xuchang University.
文摘Many liquid metals have a high boiling point,strong electrical conductivity,high thermal conductivity,and nontoxic properties,which make them ideal targets for applications in different fields such as optics,microcircuits,electronic switches,micro-electromechanical System(MEMS)devices and 3D printing manufacturing.However,owing to the generally high surface tension of these liquids,achieving uniform micro-droplets is often a challenge due to the inherent difficulties in controlling their size and shape.In this study,a gallium indium alloy(GaIn24.5)has been used in combination with a pneumatic drop-on-demand(DOD)injection technology to carry out a series of experiments.The micro-droplet forming process has been explored for different pressure and pulse width conditions.Uniform metal droplets(diameter 1080μm)have been obtained with a 1.5 kPa jet pressure,100 ms pulse width,and 50%duty ratio.The standard deviation of the measured metal droplets diameter has been found to be approximately 20μm.
文摘展开互质阵列将两个子阵完全展开,因而可在阵元数目受限情况下获得相较于均匀阵列以及传统互质阵列更大的阵列孔径。文中基于双基地展开互质阵列多输入多输出(Multiple Input Multiple Output,MIMO)雷达阵列结构,提出了基于降维多重信号分类(Multiple Signal Classification,MUSIC)算法的双基地展开互质阵列MIMO雷达离开角(Direction of Departure,DOD)、到达角(Direction of Arrival,DOA)联合估计算法。算法通过增加约束并构造代价函数的方式,将二维MUSIC算法中的穷尽搜索二维谱峰转化为求解带约束二次优化问题,先后得到DOA、DOD,并且DOD与DOA自动配对。降维思想的引入使得算法无需二维搜索,因而复杂度显著下降。同时,得益于展开互质阵列MIMO雷达形成的虚拟阵列与大幅扩展的阵列孔径,文中提出的算法亦获得了显著提升的分辨率、自由度以及低信噪比下更为优异的估计性能。此外,子阵数目的互质消除了阵元间距大于半波长可能导致的相位模糊问题。仿真验证了算法的有效性。
文摘多输入多输出(Multiple-input multiple-output,MIMO)雷达利用多个天线发送和接收信号,具有超过传统相控阵的潜在优势。本文提出一种双基地MIMO雷达中基于传播算子的离开角(Direction of departure,DOD)和到达角(Direction of arrival,DOA)估计算法。该算法利用传播因子避免了对协方差矩阵特征值分解降低了运算的复杂度,并且在低信噪比和低快拍数的情况下,该算法仍具有良好的性能。与快速多目标定位算法相比,本文算法的角度估计性能有很大的提高。文中还推导出了离开角和到达角估计的均方误差。仿真结果证明了该算法的有效性。
文摘实值处理具有降低高自由度多输入多输出(multiple-input multiple-output,MIMO)雷达角度估计大计算量的优势。但受制于阵列的共轭对称性,对于任意阵列结构的双基地MIMO雷达发射角(direction of departure,DOD)和接收角(direction of arrival,DOA)联合估计,若不做附加的预处理则无法实现实值操作,故将常规阵列实值处理的多重信号分类(multiple signal classification,MUSIC)超分辨算法推广至任意阵列结构的双基地MIMO雷达。首先根据MIMO雷达的导向矢量共轭与镜像的对等性,提取接收信号协方差矩阵的实部,并对其进行特征分解得到"目标加倍"的信号子空间及其应对的噪声子空间;然后利用Kronecker积的特性对其进行降维处理,得到搜索区域减半的一维半实值域MUSIC谱,取出目标DOD真值与其镜像代入降维Capon算法来剔除虚拟峰值得到目标DOD估计真值;最后利用特征矢量得到模糊DOA估计值,采用方向余弦差最小范数方法得到目标DOA无模糊估计值。本文算法估计性能与一维搜索复数域MUSIC相当,计算量约降50%,且能够实现DOD和DOA的自动配对。仿真结果证明了该算法的有效性。
基金The National Science Foundation(NSF)through Grants ECCS-2111056 and CMMI-1846863.
文摘Over the course of millions of years,nature has evolved to ensure survival and presents us with a myriad of functional surfaces and structures that can boast high efficiency,multifunctionality,and sustainability.What makes these surfaces particularly practical and effective is the intricate micropatterning that enables selective interactions with microstructures.Most of these structures have been realized in the laboratory environment using numerous fabrication techniques by tailoring specific surface properties.Of the available manufacturing methods,additive manufacturing(AM)has created opportunities for fabricating these structures as the complex architectures of the naturally occurring microstructures far exceed the traditional ways.This paper presents a concise overview of the fundamentals of such patterned microstructured surfaces,their fabrication techniques,and diverse applications.A comprehensive evaluation of micro fabrication methods is conducted,delving into their respective strengths and limitations.Greater emphasis is placed on AM processes like inkjet printing and micro digital light projection printing due to the intrinsic advantages of these processes to additively fabricate high resolution structures with high fidelity and precision.The paper explores the various advancements in these processes in relation to their use in microfabrication and also presents the recent trends in applications like the fabrication of microlens arrays,microneedles,and tissue scaffolds.
文摘结合分布式阵列和双基地多输入多输出(Multiple-Input Multiple-Output,MIMO)雷达的特点,提出了一种新的双基地分布式阵列MIMO雷达的接收角(Direction of Arrival,DOA)和发射角(Direction of Departure,DOD)估计方法.根据发射阵列和接收阵列的空域旋转不变特性,利用旋转不变估计技术(Estimation of Signal Parameters via Rotational Invariance Techniques,ESPRIT)获取无模糊DOA粗估计和高精度周期性模糊的DOA、DOD精估计;再利用无模糊DOA粗估计、目标的双基地距离信息以及双基地MIMO雷达的几何特点,解除DOA、DOD精估计的周期性模糊,得到高精度且无模糊的DOA和DOD估计.最后,根据ESPRIT算法原理和估计误差的概率统计特性进行算法的性能分析,给出算法基线模糊门限的近似计算方法.该算法有效地放宽了发射阵列孔径扩展程度的限制,从而提高了阵列在大孔径下的角度估计精度,且能够实现DOA和DOD估计的自动配对.仿真结果验证了所提算法和性能分析方法的有效性.
文摘Lithium element has attracted remarkable attraction for energy storage devices, over the past 30 years. Lithium is a light element and exhibits the low atomic number 3, just after hydrogen and helium in the periodic table. The lithium atom has a strong tendency to release one electron and constitute a positive charge, as Li<sup> </sup>. Initially, lithium metal was employed as a negative electrode, which released electrons. However, it was observed that its structure changed after the repetition of charge-discharge cycles. To remedy this, the cathode mainly consisted of layer metal oxide and olive, e.g., cobalt oxide, LiFePO<sub>4</sub>, etc., along with some contents of lithium, while the anode was assembled by graphite and silicon, etc. Moreover, the electrolyte was prepared using the lithium salt in a suitable solvent to attain a greater concentration of lithium ions. Owing to the lithium ions’ role, the battery’s name was mentioned as a lithium-ion battery. Herein, the presented work describes the working and operational mechanism of the lithium-ion battery. Further, the lithium-ion batteries’ general view and future prospects have also been elaborated.
文摘频控阵(Frequency Diversity Array,FDA)雷达于2006年由Antonik和Wicks提出.由于FDA雷达每个相邻的天线之间存在一个频率偏移,因此在发射阵列存在距离角度二维依赖性.而对于双基地频控阵多输入多输出(FDA-Multiple Input Multiple Output,FDA-MIMO)雷达而言,在导向矢量中耦合了波离方向、到达方向、距离(Direction Of Departure-Direction Of Arrival-range,DOD-DOA-range)三个信息,如何对三者信息进行解耦便成为研究的重点.本文针对双基地FDA-MIMO雷达的目标参数估计问题,提出了一个张量框架下的降维多重信号分类(Reduced-Dimension MUltiple SIgnal Classification,RD-MUSIC)的参数估计算法.首先,为了将发射阵列中的DOD和距离信息进行解耦,需要对发射阵列进行子阵的划分.紧接着利用高阶奇异值分解(High-Order-Singular Value Decomposition,HOSVD)算法获得信号子空间,并构建二维空间谱函数.其次,通过拉格朗日算法对空间谱进行降维,使其仅与DOA有关,从而得到DOA估计.然后利用子阵之间的频率增量来对DOD和距离信息进行解耦,同时消除相位模糊,最终得到与DOA估计自动匹配的DOD和距离估计.所提算法利用高维数据的多维结构提高了估计精度,同时能够有效地降低运算复杂度.数值实验证明了所提算法性能的优越性.
